Development of a district mental healthcare plan in Uganda

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Study Justification:
– Evidence is needed for the integration of mental health into primary care in Uganda.
– The study aims to develop a district mental healthcare plan (MHCP) in rural Uganda that facilitates integration of mental health into primary care.
– The plan can serve as a model for other rural districts in the country.
Highlights:
– A MHCP was developed with packages of care to facilitate integration at the organizational, facility, and community levels of the district health system.
– The plan includes a specified human resource mix.
– Pilot testing demonstrated the feasibility of the plan and its implications for future scaling up.
Recommendations:
– Implement the developed MHCP in the district and evaluate its effectiveness.
– Scale up the plan to other districts in Uganda.
– Address the identified barriers to scaling up the plan.
Key Role Players:
– Uganda PRIME team
– Kamuli District stakeholders (health managers, political leaders, health workers, patients, carers, lay people)
Cost Items for Planning Recommendations:
– Resources required to implement the MHCP (estimated using the WHO mhGAP costing tool)
– Training materials and resources for health workers
– Monitoring and evaluation activities
– Communication and dissemination of the plan

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is based on mixed methods, including a situational analysis, qualitative studies, theory of change workshops, and partial piloting of the plan. The abstract provides a clear description of the processes involved in developing the district mental healthcare plan in Uganda. However, to improve the strength of the evidence, the abstract could include more specific details about the findings and outcomes of the plan, such as the impact on mental health outcomes and the effectiveness of the packages of care. Additionally, including information about the sample size and demographics of the participants in the qualitative studies would provide more context and enhance the credibility of the evidence.

Background Evidence is needed for the integration of mental health into primary care advocated by the national health sector strategic investment plan in Uganda. Aims To describe the processes of developing a district mental healthcare plan (MHCP) in rural Uganda that facilitates integration of mental health into primary care. Method Mixed methods using a situational analysis, qualitative studies, theory of change workshops and partial piloting of the plan at two levels informed the MHCP. Results A MHCP was developed with packages of care to facilitate integration at the organisational, facility and community levels of the district health system, including a specified human resource mix. The partial embedding period supports its practical application. Key barriers to scaling up the plan were identified. Conclusions A real-world plan for the district was developed with involvement of stakeholders. Pilot testing demonstrated its feasibility and implications for future scaling up.

Kamuli, the implementation district for PRIME, is a typical rural district in Eastern Uganda, with a population of approximately 500 800 people.8 The district has a fertility rate of 6.7, higher than the national average of 6.2 children per woman; a maternal mortality rate of 347 per 100 000 live births, compared with the national average of 438 per 100 000 live births and an infant mortality rate of 79 per 1000 live births, compared with the national average of 54 per 1000 live births.9–11 The district was chosen out of the 112 districts in Uganda (a country with a population of 35.4 million people)11 mainly because it was typical of many rural districts in the country, with inadequate staffing and limited mental health service provision at primary care level. It could therefore form a model district if assisted to develop and operationalise its MHCP. Kamuli is a peaceful district and was not affected by insurgence in Northern Uganda. Administratively, the district is made up of two counties, ten subcounties and a number of parishes and villages (online Fig. DS1). Like all other districts, healthcare in Kamuli is offered at five levels of care, in line with the national policy. The process of developing the MHCP for the district was the joint effort of the Uganda PRIME team and Kamuli District stakeholders; a mix of both men and women, including 9 health managers, 6 political leaders, 37 health workers, 10 patients, 14 carers and 21 lay people. First, a situational analysis of the district healthcare system was conducted to gain some insight into the organisation of the healthcare system and the available resources in the district.12 This was followed by formative research to gather views and perceptions of the stakeholders on provision and utilisation of mental healthcare in the district. Data were collected using a generic interview guide developed by the consortium with five broad themes: demand/access, delivery, recovery, accountability and stakeholder views on how the research generated by PRIME could be used for policy and practice in Uganda. Focus-group discussions and individual in-depth interviews were conducted with primary healthcare workers, community health workers/village health teams, people with mental health problems, other members of the community and members of the district administration and district health management team. These participants were purposively selected as key informants who had expertise in a particular area, or who represented key stakeholder groups for mental health in the district. In-depth interviews and focus-group discussions were facilitated by two PRIME project staff members (the coordinator and research officer), who are clinical psychologists with Masters degrees in clinical psychology. These facilitators were employed by Makerere University in Kampala, and visited the Kamuli district for the purpose of data collection. In total, 14 focus-group discussions, with an average of 7 participants per focus-group discussion (n = 84) and 13 in-depth interviews were conducted (n = 13). The focus-group discussions and in-depth interviews were transcribed verbatim and those in the local language (Luganda) were translated into English. Data were coded with the help of NVivo9, a qualitative data analysis package and analysed using a content analysis framework.13 Phase two involved the development of the theory of change (ToC) map for the MHCP. ToC is the articulation of the underlying beliefs and assumptions that guide a service delivery strategy and are believed to be critical for producing change and improvement.14,15 A generic PRIME ToC map was initially developed in consultation with the partners in all PRIME countries sites.16 Equipped with baseline information from the situational analysis and findings from the formative research, the PRIME Uganda team adapted the generic PRIME ToC map to the situation in Kamuli. This was done by conducting two ToC workshops with various stakeholders, including 4 administrators, 8 health managers and 14 health service providers.17 These were some of the stakeholders who had earlier participated in the in-depth interviews and focus-group discussions. The purpose of the first workshop was to orient the participants in doing ToC mapping, and to agree on feasible outcomes, indicators of progress and strategies for the MHCP that would lead to the broad programme goals of improving health, social and economic outcomes of people with PRIME-prioritised mental disorders: depression (including maternal depression), alcohol use disorders, psychosis and epilepsy. A ToC map was subsequently drafted based on data from the formative research and the ToC workshops with the guidance of PRIME members. This map was systematically reviewed and finalised in the second workshop. The rationale for using ToC methodology is that it ensures a theory-driven approach to the development, evaluation and implementation of interventions.17 The MHCP was subsequently developed using the generated ToC map that has been published elsewhere in this supplement.16 Through an iterative consultation process, the PRIME team worked with the district health management team to translate information in the ToC map into five packages of care earlier agreed on in the consortium. These packages include: awareness and knowledge enhancement, detection, treatment, recovery and programme management. For each of the packages, strategic objectives, activities, roles and responsibilities as well as indicators of progress were developed for each of the three different levels of care (i.e. organisational, health facility and community levels). The human resources (cadre and numbers) to implement the plan was derived from the situational analysis report and based on the existing staff establishment. The plan was costed using the World Health Organization (WHO) Mental Health Gap Action Programme (mhGAP) costing tool, initially developed to estimate the cost of implementing and scaling up the core intervention of the mhGAP intervention guide,18 and subsequently adapted for use in PRIME. More details of the tool are provided by Chisholm et al in this supplement.19 For the purposes of the Kamuli MHCP, the aim of the tool was to estimate the overall resource needs and cost implications of a scaled-up package of mental healthcare in Uganda. In developing the plan, the resources required to implement it were identified, estimated and fed into the mhGAP costing tool for each of the priority disorders in order to determine the cost of implementation and scaling up. The plan was piloted between August 2013 and February 2014 to evaluate its feasibility and identify any possible challenges before rolling it out to the entire district. This was done at two healthcare delivery levels (organisational and health facility levels); covering four out of the five packages. At organisational level, the piloting exercise covered two packages: awareness raising and programme management. At facility level, the packages covered included awareness and knowledge enhancement, detection and treatment. Evaluation was done at the health facility level, using both qualitative and quantitative methods, and covering 12 out of the 34 health facilities. The focus of the evaluation was on training satisfaction and ability to identify the priority conditions. Training was conducted using the mhGAP intervention guide training materials.18 The mhGAP intervention guide is a clinical guideline designed for use by primary care practitioners, with algorithms to assist diagnosis and treatment of eight priority conditions.20 The first 25 health workers to be trained were followed up 3 months later in the field and subjected to the mhGAP self-reported competence questionnaire (http://bit.ly/competencequest). This questionnaire is administered to health workers (prescribers) before and after receiving training in the mhGAP intervention guide. The questionnaire assesses nine self-reported competence areas: diagnosis, management of emergencies, prescription, monitoring, follow-up, provision of advice about the condition, referral, improving individual/community access to treatment and provision of psychological support. Only 17 of them participated in this evaluation exercise, as the remaining 8 were reportedly away from their duty stations at the time of this evaluation. The number of health workers who reported improvement in the core areas is as follows: diagnosis (15), management of emergencies (8), prescription of antidepressants (16), monitoring (14), follow-up (16), provision of advice about the condition (16), referral (16), improving individual access to treatment (14) and provision of psychological support (15). In addition, four in-depth interviews (two with clinical officers and two with nurses) and one focus-group discussion (with primary healthcare nurses) were also held for feedback and assessing the impact of the training on the health workers’ practice. Finally, health management information system (HMIS) records from 13 health facilities were reviewed with a particular focus on the mental health indicators, making a comparison of 6 months before and 6 months after the training, in order to be able to track the trend in detection and reporting for mental health conditions. The HMIS records the number of patients treated for the various conditions at the different health facilities. This information is sent to the district health office on a monthly basis. These records were utilised as this provides a sustainable source of data to continue to monitor MHCP implementation over time. The results of the piloting were shared with some of the key stakeholders in the district and used in the processing of refining the MHCP.

Based on the provided information, here are some potential innovations that can be used to improve access to maternal health:

1. Telemedicine: Implementing telemedicine services can help overcome geographical barriers and provide access to maternal health services in remote areas. This technology allows pregnant women to consult with healthcare professionals remotely, reducing the need for travel and increasing access to prenatal care.

2. Mobile health (mHealth) applications: Developing mobile applications that provide information and resources related to maternal health can empower women with knowledge and support. These apps can provide guidance on prenatal care, nutrition, and breastfeeding, as well as reminders for appointments and medication.

3. Community health workers: Training and deploying community health workers who are specifically focused on maternal health can improve access to care in rural areas. These workers can provide education, support, and referrals for pregnant women, ensuring they receive the necessary care throughout their pregnancy.

4. Transportation solutions: Addressing transportation challenges can greatly improve access to maternal health services. Implementing innovative transportation solutions such as mobile clinics, ambulances, or community-based transportation networks can help pregnant women reach healthcare facilities in a timely manner.

5. Public-private partnerships: Collaborating with private sector organizations can help improve access to maternal health services. Partnering with private healthcare providers, pharmaceutical companies, or technology companies can bring additional resources, expertise, and innovation to expand and improve maternal health services.

6. Maternal health financing models: Developing innovative financing models, such as microinsurance or community-based health financing schemes, can help overcome financial barriers to accessing maternal health services. These models can provide affordable and accessible healthcare coverage for pregnant women, ensuring they receive the care they need.

7. Maternal health information systems: Implementing robust information systems that track and monitor maternal health indicators can help identify gaps in access and quality of care. These systems can provide real-time data to inform decision-making and resource allocation, leading to more targeted interventions and improved access to maternal health services.

It is important to note that the specific recommendations for improving access to maternal health will depend on the context and specific needs of the population.
AI Innovations Description
The recommendation to improve access to maternal health based on the described research is the development of a district mental healthcare plan (MHCP) in rural Uganda. This plan aims to integrate mental health into primary care and improve the overall health outcomes of people with mental disorders, including maternal depression. The development of the MHCP involved a mixed methods approach, including situational analysis, qualitative studies, theory of change workshops, and partial piloting of the plan at two levels. The plan includes packages of care to facilitate integration at the organizational, facility, and community levels of the district health system, along with a specified human resource mix. The piloting of the plan demonstrated its feasibility and provided insights for future scaling up. The MHCP was developed in collaboration with stakeholders, including health managers, political leaders, health workers, patients, carers, and lay people. The plan was costed using the World Health Organization (WHO) Mental Health Gap Action Programme (mhGAP) costing tool. The piloting of the plan involved training health workers using the mhGAP intervention guide and evaluating their competence in diagnosing and managing mental health conditions. Health management information system (HMIS) records were also reviewed to track the trend in detection and reporting of mental health conditions before and after the training. The results of the piloting were used to refine the MHCP.
AI Innovations Methodology
Based on the provided information, it seems that the request for innovations to improve access to maternal health is not directly related to the content. However, I can provide a brief methodology to simulate the impact of recommendations on improving access to maternal health.

Methodology to Simulate the Impact of Recommendations on Improving Access to Maternal Health:

1. Define the recommendations: Identify the specific recommendations or interventions that are intended to improve access to maternal health. These could include initiatives such as increasing the number of healthcare facilities, improving transportation infrastructure, implementing telemedicine solutions, or enhancing community health worker programs.

2. Collect baseline data: Gather relevant data on the current state of maternal health access in the target area. This may include information on maternal mortality rates, healthcare facility coverage, transportation availability, and other relevant indicators.

3. Develop a simulation model: Create a simulation model that represents the target population and healthcare system. This model should incorporate the baseline data and the proposed recommendations. The model should simulate the impact of the recommendations on various outcome measures, such as the number of women accessing prenatal care, the rate of skilled birth attendance, and the reduction in maternal mortality.

4. Validate the model: Validate the simulation model by comparing its outputs with real-world data or expert opinions. This step ensures that the model accurately represents the target population and healthcare system.

5. Run simulations: Use the validated simulation model to run multiple simulations with different scenarios. This could involve varying the implementation strategies, resource allocation, or timing of the recommendations. Each simulation should provide insights into the potential impact of the recommendations on improving access to maternal health.

6. Analyze the results: Analyze the simulation results to identify the most effective recommendations and strategies for improving access to maternal health. This analysis should consider factors such as cost-effectiveness, scalability, and sustainability.

7. Refine and iterate: Based on the analysis of the simulation results, refine the recommendations and strategies as needed. Iterate the simulation process to further explore different scenarios and optimize the impact on improving access to maternal health.

8. Communicate findings: Present the findings of the simulation study to relevant stakeholders, such as policymakers, healthcare providers, and community organizations. Use the results to advocate for the implementation of the most effective recommendations and strategies.

It is important to note that the methodology described above is a general framework and may need to be adapted based on the specific context and resources available for the simulation study.

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